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6 factors crucial to the success of industrial IoT in manufacturing

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As manufacturers digitally transform their value chains, connected devices will play a major role. Getting it right requires a laser focus on six key areas.

The internet of things (IoT) connects physical machines and equipment in a factory

to the digital world of cloud, data analytics and artificial intelligence (AI). It enables

you to collect more data, analyze the information quickly and make better business

decisions.

Forward-thinking manufacturers already know they need to bring IT closer to

operational technologies that control machines and equipment. Traditionally, these

technologies were managed by separate departments in relative isolation. Leaders,

such as food and beverage giant Lion, have merged the teams to create a single

integrated technology function to leverage synergies.

The next step is to harness technology to optimize the business and drive innovation.

Industry 4.0 advances in manufacturing are setting the standard for creating the

smart factory and supply chain of the future using industrial IoT (IIoT), analytics,

cloud computing and cyber physical systems. Manufacturers can now consider

business model innovation and new revenue streams as they leverage the deluge of

IoT data. This is often called the servitization of the industry.

The importance of Industry 4.0 and the IIoT is well understood, but how do you start

implementing these concepts to maximize your chances of creating real value?

Critical success factors

There are six critical success factors organizations need to consider to successfully

use IIoT in their digital transformation initiatives (Figure 1).

Figure 1. IIoT critical success factors

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Business benefits

Early discussions about IIoT primarily focused on the technology and what it could

do, rather than on the business value IIoT could deliver. This is not surprising; IoT

technologies’ cool factor has clearly captured people’s attention. More recently, the

conversations have shifted to the variety of business benefits IIoT can deliver.

Business model innovation. Companies can create new products and

services to generate additional revenue streams. Machines with IIoT

sensors can gather huge amounts of data, and advanced analytics

can transform it into “smart data” – that is, digital information that is

formatted so that it can be acted upon at the collection point before

being sent to a downstream analytics platform. Smart data can support

decision making or can trigger actions automatically, and this value

can be monetized. One of the most popular use cases is predictive

maintenance of factory assets. If the organization servicing the assets

is able to predict equipment failure, it can offer the predictions as an

additional paid service.

Customer experience. IIoT can help make products and services

more attractive. IIoT-enabled parts, for example, are easier to find in a

warehouse when used in conjunction with an indoor navigation system

that can lead warehouse staff directly to their location. A smart product

can determine when service levels are being exceeded or when it’s time

for a maintenance check, potentially preventing a breakdown. The data

generated by smart products also can be used to improve the service

experience in the after-sales market by learning about customer usage

and preferences.

Operational excellence. Sensors and actuators can closely monitor

the manufacturing process and products as they travel through a

factory, enabling real-time control of the production system. While

control systems have monitored factories for decades, it is now possible

to make those systems more intelligent by feeding IIoT and business

data into smart algorithms. In supply chain operations, sensors and IIoT

devices can track and trace products on their way from the factory to

the customer, anywhere in the world.

Environmental stewardship. Traditionally, lower cost and

higher revenue have been the only measurements of success for

manufacturers, but today they are also being measured on corporate

social responsibility. This means that the environmental impact of the

production process and the products in use are areas of value creation.

Examples of value include energy savings that result in a lower carbon

footprint as well as the monitoring of air, soil and water quality. IIoT also

can help monitor the environment, triggering alerts and even shutting

down operations if required.

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“The disruptive potential of IoT resides in its ability to turn businesses inside-out, transform products into services, transform services into learning architectures and make us completely rethink what the organization of the future may look like.”

– John Seely Brown, Independent Co-Chairman, Deloitte LLP Center for the Edge

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Worker health and safety. Risks are commonplace. Managing the

risks effectively avoids the human tragedy and financial loss associated

with accidents. IIoT sensors can be used to monitor the immediate

environment around a worker, but can also measure a person’s vitals,

such as heart rate, fatigue or stress. Knowing where an employee is

located — together with health data, defined operational limits and data

analytics — can help detect risks and issues in the work environment.

Compliance. In many cases, manual inspections can be replaced by

IIoT technologies. For fixed assets in a manufacturing plant, this can

be achieved through sensors and through autonomous vehicles with

sensors, cameras, microphones and other technology needed to perform

inspections. In larger facilities, drones can inspect the outside areas.

Inspectors responsible for compliance can use IIoT systems to increase

the inspection frequency and therefore detect compliance issues early

on.

Strategic alignment

Some organizations have set up digital innovation labs without clear strategic

direction or technology roadmaps, and the result is often proofs of concept that don’t

have value for the business or are not supported by their technology functions.

For IIoT to have a positive impact on the organization, it needs to be aligned with the

overall business and technology strategy. The business strategy provides guidance

on goals and objectives, while the technology strategy identifies constraints around

technology choices. The best way to ensure strategic alignment is to create an IoT

strategy that considers current strategies and also drives changes to those strategies.

For example, if IIoT provides a new way to ensure the health and safety of factory

workers, the human resources strategy should consider this. Strategic alignment is

key, but it is not a one-way street.

Business process focus

The discussion around IIoT is dominated by data analytics, machine learning and

AI. Business processes may not be the most exciting topic, but they are still the core

of any organization and define how the business operating model is structured. An

emerging focus in the manufacturing industry is the integration of IIoT solutions into

business processes. In an IoT report, McKinsey notes that the missing integration of

IoT solutions into existing business workflows is a top IoT capability gap.1

IIoT software vendors may claim their products integrate with business systems, but

simply passing data to a business system is not the same as creating an end-to-end

business process. Using that process, organizations will have an increased number

of smart things in their factory, increased levels of automation and more complex

supply chains. The expectation is to make everything work together effectively in a

way that is dramatically better than today.

1 https://www.mckinsey.com/global-themes/interet-of-things/our-insights/taking-the-pulse-of-enterprise-iot

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“The Internet of Things will transform business processes into IoT-enabled business processes, where things and humans collaborate. We will witness an increased autonomy of smart things that will be able to navigate their own ways through our factories, distribution centres and supply chains, analysing context-sensitive multiple data points to drive highly individualised business processes.”

– Michael Rosemann Executive Director Corporate Engagement, QUT

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Operating model changes

Many IoT industry participants talk about the convergence of IT and operational

technology, meaning that the management of business systems and factory

automation technologies will converge. IT and operational technology convergence

does not only mean a convergence of technologies, but also that you can optimize

collaboration between your office floor and your factory floor. In many cases, this will

lead to changes in the business operating model and will require new capabilities in

your organization to manage.

Another aspect is the creation of value networks, which are purpose-built partner

ecosystems with the customer in the middle. ETH Zurich and Bosch SI developed the

concept of an “IoT Business Model Builder” that describes how the idea of business

model innovation as part of Industry 4.0 can be implemented.

The concept of value networks leads to an extended enterprise and is necessary

because end-to-end IIoT solutions are even more complex than separate IT and

operational technology solutions were in the past, and require a very close

collaboration between the value network stakeholders.

Capability uplift

With changes to the technology landscape and operating model, employees need to

learn new skills as their roles change. It is important that people understand IIoT and

Industry 4.0 concepts from both a business and technology perspective, establishing

a common language to minimize the risk of misunderstanding.

For the next level of detailed understanding of IIoT, focused programs that advance

employees’ capabilities need to be developed. In these programs, active participation

of the partner ecosystem, or value network, should be considered. A common

learning experience can improve and drive day-to-day collaboration.

Consider how educational and training programs can affect certain roles in a

manufacturing company and close skills gaps. Chief operating officers can get

new insights into the operation of the business, but they will want to understand

what the new data is and how to incorporate it into their decision making. Chief

technology officers will be flooded with new technologies and will want to select the

ones relevant for the business. They will want to learn about functionalities provided

by IIoT gateways, low-power WAN, sensor boards and IoT platforms. Maintenance

technicians will want to understand why predictive maintenance is important, and

how IIoT and data analytics will enable them to be more proactive with maintenance

inspection activities.

End-to-end security

Vulnerabilities in self-driving cars get a lot of media attention and illustrate the

security concerns around IIoT. Smart factories are also at risk, and although

technology vendors are quick to provide security patches, the risks show that security

is often not built into the design of a production system. One of the reasons is that

those solutions were closed systems for decades and relatively safe from intruders.

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“One of the major challenges that companies face when trying to solve for revenue generating IoT solutions is the fact these solutions often require disrupting the same business model that made them successful to date.”

– Tom Galizia, Principal, U.S. Technology Strategy and Architecture Leader, Deloitte Consulting LLP

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In the past, manipulating machines in a factory typically required physical access

to the facility, but by linking assets to the internet and deploying IIoT capabilities,

facilities are now exposed to new security risks. New approaches for cyber-physical

systems are being developed that include authentication and encryption capabilities

built into hardware, real-time analytics of network traffic, and IIoT gateways that

serve as protective shields for factory equipment, similar to the way firewalls perform

in IT networks. With the convergence of IT and operational technology, “security by

design” is becoming a key decision criterion as companies choose technologies.

Industry 4.0 is a journey — how can DXC Technology help?

Industrial IoT is not a single solution that is implemented by one big project. It is a

journey along a maturity curve that needs to be planned strategically using the six

critical success factors: business value, strategic alignment, business process focus,

operating model changes, capability uplift, and end-to-end security. DXC can help

organizations along the journey with our industry insights and deep technology

expertise. We leverage capabilities and experiences from around the globe to

customize our solutions to the needs of our clients.

Learn more at www.dxc.technology/manufacturing

www.dxc.technology

About DXC Technology

DXC Technology (DXC: NYSE) is the world’s leading independent, end-to-end IT services company, serving nearly 6,000 private and public-sector clients from a diverse array of industries across 70 countries. The company’s technology independence, global talent and extensive partner network deliver transformative digital offerings and solutions that help clients harness the power of innovation to thrive on change. DXC Technology is recognized among the best corporate citizens globally. For more information, visit dxc.technology.

© 2018 DXC Technology Company. All rights reserved. November 2018

About the author

Peter Klement is chief technologist for manufacturing in

DXC Technology’s Digital Transformation Consulting, with a

focus on Industry 4.0 and industrial IoT. His mission is to help

organizations strategically transform their businesses with the

help of digital technologies such as IoT, data analytics and

cloud. Peter looks at new technologies from the perspective of

business benefits and how they can optimize operating models

and foster business model innovation.